Again: be aware of your assumptions. Especially us datavis nerds often have the dangerous assumption that everyone is as crazy about datavis as we are. I mean, just think back to my grandiose introduction of visualization in the beginning here.
Teaching — Enrico Bertini. I have taught Information Visualization at NYU Tandon every year since 2012.

The course focuses on how to design, develop and evaluate interactive data visualization solutions for complex data analysis problems. This page links to material I developed for the course.
Julia Buntaine: Visualizing science: bridging the science-art gap. A History of DataViz – info we trust.
After examining the history of data visualization greats I have decided to collect my learnings in the style of history’s data visualization greats.

The first of these visual summaries is presented and discussed below. You can explore the entire series here. A map to guide you through the early developments of data visualization, including cartoons of 75 key charts, in the style of John Ogilby’s 1675 Road Atlas. This image is sized for web-consumption and is only a fraction of the actual piece which can be properly enjoyed via: ACCESS BIG 31mb JPG HERE or GET THE PRINT(in many formats + other fun items) John Ogilby published his BRITANNIA road atlas, the first of its breadth and quality, in 1675.
Plant Image Analysis - Software. What Causes the Smell of New & Old Books?
Everyone’s familiar with the smell of old books, the weirdly intoxicating scent that haunts libraries and second-hand book stores.

Similarly, who doesn’t enjoy riffling through the pages of a newly purchased book and breathing in the crisp aroma of new paper and freshly printed ink? As with all aromas, the origins can be traced back to a number of chemical constituents, so we can examine the processes and compounds that can contribute to both. As far as the smell of new books goes, it’s actually quite difficult to pinpoint specific compounds, for a number of reasons.
Vintage InfoPorn No.1. My conceit, when I started making infographics, was simple.

I believed this was a *new way* of expressing and visualizing information, a thoroughly modern and zeitgeisty fusion of data and design. Oh you muppet David… These infographics were created by students of American African-American activist W.E.Dubois in 1902. They’re so modern looking! Right down to the type.
History of Graphic Design. The Surprising History of the Infographic. 5 Tips for Learning to Code for Visualization. There are many click-and-play software programs, solutions, and tools to help you visualize your data.

They can be super helpful and you can get a lot done without a single line of code. However, being able to code your own visualization carries its own benefits like flexibility, speed, and complete customization. It’s fun — once you know what you’re doing. And that’s the kicker. It takes time to learn to program, and most of us don’t have the minutes to spare. Here are some tips to get you started, based on my own experiences with R, and more recently, the JavaScript library d3.js. Use the software you’re most comfortable with Learning to code for visualization doesn’t mean abandoning the tools you’re already familiar with.

You don’t have to do everything in R or in JavaScript.
The Power of Looking Closely. At least in the US, it’s the start of a long holiday weekend, and elsewhere there are things like the Euros and Brexit to distract people from the internet, alas.

I wanted to share this video by Amy Herman on “Visual Intelligence,” based on her book Visual Intelligence: Sharpen Your Perception, Change Your Life, which in turn was based on a project she used to do at the Frick Collection while she was training medical students how to look at art.
39 studies about human perception in 30 minutes. Bars and pies for proportions Much is said about the relative merits of bars and circles for showing proportions.

All five of these studies legitimize the use of pie charts when conveying proportions and some even show their superiority over bar charts.
The Trials and Tribulations of Data Visualization for Good. “I love big data.

It’s got such potential for storytelling.” At DataKind, we hear some version of this narrative every week. As more and more social organizations dip their toes into using data, invariably the conversation about data visualization comes up. There is a growing feeling that data visualization, with its combination of “engaging visuals” and “data-driven interactivity”, may be the magic bullet that turn opaque spreadsheets and dry statistics into funding, proof, and global action.

However, after four years of applying data-driven techniques to social challenges at DataKind, we feel that data visualization, while it does have an important place in our work, is a mere sliver of what it takes to work with data. Ugh.
Visualization as Process, Not Output. “Please make me a visualization.” I get a lot of emails that say this or some variation of it.

They tend to make me think of other requests that could be made in the same form, like: “Please make me a roast beef sandwich.” Or:
Diagramism. Data Visualization With Knoema. Anyone who’s had to deal with large amounts of data will be well aware that sometimes a visual can be extremely helpful in understanding that data. This map of states party to the Convention on the Rights of the Child that I tweeted out last November is a case in point: Even if I were particularly skilled at creating visualizations, I might not always have the time available to do so, or to locate the data I need.
Sketching with Data Opens the Mind’s Eye — Accurat studio. As Heller observes in the introduction “Making enticingly accurate infographics requires more than a computer drafting program or cut-and-paste template, the art of information display is every bit as artful as any other type of design or illustration, with the notable exception that it must tell a factual or linear story”.

The fascination for what lies behind any creative process is no new thing, and the book is a terrific anthology of beautiful examples from international artists: the finished works of the are presented alongside with the designers’ working sketches; but when does exactly drawing become design? What does sketching do to a designer’s mind and how does it affect the process of working with data? I am an information design myself. I have been trained as an architect, but soon after my graduation I started working with information in a visual way.
Beautiful Reasons — Accurat studio. To be a designer you have to find new languages, new ways of entertaining people; and working with data you also have to make visuals that can become magnetic to people that are not familiar with data practices.

We believe that, sometimes, the act of loading an analytical representation with emotional investment produces attention rather than distraction, creates worlds that are evocative and nameless at the same time, able to inspire sensations, as long as we always respect the values in the data and we don’t manipulate the information. To this regard, we can define successful designs as the ones able to balance convention (i.e. familiar forms our minds are already familiar with) and novelty: new features that can engage and delight people in the hope they will stick around our visualizations a bit longer, and in the hope we can help the conversations in our fields moving forward.
Learning to See: Visual Inspirations and Data Visualization — Accurat studio. As Brainpickings points out, some interesting patterns emerge from this dense piece: “Japan, held as a paragon of technological innovation, actually attracts very few foreign researchers.

Denmark, despite a GDP budget significantly larger, doesn’t do too much better than countries like Belgium, France and Germany. Canada, Australia, the United States, and Switzerland attract — and export — the greatest number of scientists.”
Visualising Painters' Lives on Behance. Data is the Latest Medium for Creating Beautiful, Meaningful Art. Although much of their artwork looks random, that’s far from reality. A growing number of “data artists” are creating conceptual work using information collected by personal data trackers, mobile apps, scientific experiments and even hand written notes.

Translating that data using creative metrics and physical mediums, their works reveal patterns hidden in nature and ourselves, often revealing it through the lens of colorful sculptures or images. Some artists, like Laurie Frick, envision a world transformed and beautified by our wealth of data. Others see it as an interpretive tool used to see things previously hidden to our senses.
Little boxes. Intermental. Simple Visualizations with D3plus. Announcing the Information is Beautiful Awards Longlist. Showcase. Subtleties of Color (Part 1 of 6) : Elegant Figures : Blogs. Introduction The use of color to display data is a solved problem, right?

The Science of Visualization - SA Visual - Scientific American Blog Network. Infographics. The book contains 99 separate infographics split into nine sections.
The Architecture of a Data Visualization — Accurat studio. 1. Composing the main architecture of the visualizationComposing the main architecture: this acts as the formalized base through which the main story will be mapped and displayed, upon this, one will see the most relevant patterns emerging from the story: the essential “map” that conceptually identifies where we are.